Motion Control of a Flexible-Towed Underwater Vehicle Based on Dual-Winch Differential Tension Coordination Control by Hongming Wu, Xiong Li, Kan Xu, Dong Song, Yingkai Xia, Guohua Xu

“…Stability proof of the proposed algorithms was provided. Extensive numerical simulations demonstrate the effectiveness of the control strategies. …”
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Predicting nosocomial pneumonia of patients with acute brain injury in intensive care unit using machine-learning models by Junchen Pan, Zhen Yue, Jing Ji, Yongping You, Liqing Bi, Yun Liu, Xinglin Xiong, Genying Gu, Ming Chen, Shen Zhang

“…Despite differences in populations and algorithms, the models we constructed demonstrated reliable predictive performance.…”
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Reassortment Dynamics: Phylogeography and Evolution of H4N9 Influenza Viruses by Nataliia A. Bobrova, Ekaterina D. Lisenenkova, Ekaterina S. Avsievich, Olga N. Mityaeva, Pavel Yu Volchkov, Andrey A. Deviatkin

“…Several computational approaches, including phylogenetic reconstructions and reassortment detection algorithms (PDDM and PDCP), were used to identify phylogenetic incongruences. …”
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Game Interactive Learning: A New Paradigm towards Intelligent Decision-Making by Junliang Xing, Zhe Wu, Zhaoke Yu, Renye Yan, Zhipeng Ji, Pin Tao, Yuanchun Shi

“…It then optimizes the learning objectives from equilibrium analysis using reformed machine learning algorithms to compute and pursue promising decision results for practice. …”
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Leveraging dendritic complexity for neuromorphic computing by Suma G Cardwell, Mark Plagge, Luke Parker, Claire E Plunkett, David Munkvold, Paloma T Gonzalez-Bellido, Scott Koziol, Conrad James, Frances S Chance

“…Beyond-von Neumann computing approaches are necessary to sustain the growth of microelectronics and the increasing appetite for artificial intelligence/machine learning algorithms. Neuromorphic computing is an emerging paradigm that takes inspiration from the brain to provide a path forward to improve the computational efficiency and computational density of next-generation computing architectures. …”
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Modeling the impact of climate change on suitable areas for the underutilized crop Cyperus esculentus (tiger nut) and implications for production expansion and conservation in Togo... by Koffi Kibalou Palanga, Anissou Bawa, Jacques Idohou Kadjogbé Ayena, Dowo Michée Adjacou, Thierry Dèhouégnon Houehanou, Gérard Nounagnon Gouwakinnou, Armand Kuyema Natta

“…This study aims to model its current and future distribution using the MaxEnt and Bioclim algorithms, incorporating environmental variables and occurrence data from the field and the GBIF database. …”
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A Versatile, Machine-Learning-Enhanced RF Spectral Sensor for Developing a Trunk Hydration Monitoring System in Smart Agriculture by Oumaima Afif, Leonardo Franceschelli, Eleonora Iaccheri, Simone Trovarello, Alessandra Di Florio Di Renzo, Luigi Ragni, Alessandra Costanzo, Marco Tartagni

“…Thanks to the flexibility of the system’s architecture, which embeds a Linux operating system, we can easily embed machine learning (ML) algorithms and predictive models for information detection. …”
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Real-time classification of EEG signals using Machine Learning deployment by Swati CHOWDHURI, Satadip SAHA, Samadrita KARMAKAR, Ankur CHANDA

“…By monitoring the students' electroencephalography (EEG) signals and employing machine learning algorithms, this study proposes a comprehensive solution for addressing this challenge. …”
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Estimation of water storage changes in a tropical lake-floodplain system through remote sensing by Thijs de Klein, Victor Bense, Syed Mustafa

“…A collection of optical remote sensing and Synthetic Aperture Radar (SAR) scenes is used in combination with supervised classification algorithms and topographical data to derive lake volumes for the period 1984–2023, which are analyzed for trends and correlation with satellite-derived climate data. …”
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Feature Selection and Hyper-parameter Tuning Technique using Neural Network for Stock Market Prediction by Karanveer Singh, Rahul Tiwari, Prashant Johri, Ahmed A. Elngar

“…The existing stock market prediction focused on forecasting the regular stock market by using various machine learning algorithms and in-depth methodologies. The proposed work we have implemented describes the new NN model with the help of different learning techniques like hyperparameter tuning which includes batch normalization and fitting it with the help of random-search-cv. …”
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The influence of pH and temperature on benthic chlorophyll-a: Insights from SHAP-XGBoost and random forest models by Sangar Khan, Noël P.D. Juvigny-Khenafou, Tatenda Dalu, Paul J. Milham, Yasir Hamid, Kamel Mohamed Eltohamy, Habib Ullah, Bahman Jabbarian Amiri, Hao Chen, Naicheng Wu

“…There is little information on machine learning predictive models of benthic chl–a and input parameters in lotic ecosystems, and to fill this gap, we predict benthic chl–a levels in China's Thousand Islands Lake (TIL) watershed using machine learning algorithms. Water samples for nutrient and metal analysis were collected across 147 sites in the TIL catchment. …”
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Systematic review of AI/ML applications in multi-domain robotic rehabilitation: trends, gaps, and future directions by Giovanna Nicora, Samuele Pe, Gabriele Santangelo, Lucia Billeci, Irene Giovanna Aprile, Marco Germanotta, Riccardo Bellazzi, Enea Parimbelli, Silvana Quaglini

“…After article retrieval, a tagging phase was carried out to devise a comprehensive and easily-interpretable taxonomy: its categories include the aim of the AI/ML within the rehabilitation system, the type of algorithms used, and the location of robots and sensors. …”
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Nonharmonic Analysis-Based Detection-Performance Improvement Technique for Distance Estimation of 24 GHz Narrowband FMCW Radar by Shotaro Koyama, Tsubasa Suzuki, Junpei Tsutsumi, Taisei Matsuyama, Takumu Ikenaga, Fumiya Shinohara, Masaya Hasegawa, Shigeki Hirobayashi, Kazuo Yoshida

“…Furthermore, at low-range resolutions, the power spectral density (PSD) of the fast Fourier transform and multiple signal classification algorithms typically used for distance measurements often suffer from sidelobe interference between the signals. …”
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In vivo variability of MRI radiomics features in prostate lesions assessed by a test-retest study with repositioning by Kevin Sun Zhang, Christian Jan Oliver Neelsen, Markus Wennmann, Thomas Hielscher, Balint Kovacs, Philip Alexander Glemser, Magdalena Görtz, Albrecht Stenzinger, Klaus H. Maier-Hein, Johannes Huber, Heinz-Peter Schlemmer, David Bonekamp

“…Abstract Despite academic success, radiomics-based machine learning algorithms have not reached clinical practice, partially due to limited repeatability/reproducibility. …”
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Predicting and Preventing School Dropout with Business Intelligence: Insights from a Systematic Review by Diana-Margarita Córdova-Esparza, Juan Terven, Julio-Alejandro Romero-González, Karen-Edith Córdova-Esparza, Rocio-Edith López-Martínez, Teresa García-Ramírez, Ricardo Chaparro-Sánchez

“…The results highlight a wide range of predictive tools and methodologies, notably data visualization platforms (e.g., Power BI) and algorithms like decision trees, Random Forest, and logistic regression, demonstrating effectiveness in identifying dropout patterns and at-risk students. …”
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Metabolic Plasticity and Transcriptomic Reprogramming Orchestrate Hypoxia Adaptation in Yak by Ci Huang, Yilie Liao, Wei Peng, Hai Xiang, Hui Wang, Jieqiong Ma, Zhixin Chai, Zhijuan Wu, Binglin Yue, Xin Cai, Jincheng Zhong, Jikun Wang

“…The protein–protein interaction network identified three consensus hub genes across five topological algorithms (<i>CCNA2</i>, <i>PLK1</i>, and <i>TP53</i>) that may be involved in hypoxia adaptation. …”
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Hybrid Active and Passive Cable Contour Shielding of Magnetic Fields of Double-Circuit Overhead Power Lines by Kuznetsov B.I., Kutsenko A.S., Nikitina T.B.

“…The solution to the minimax vector optimization problem is calculated based on multi-particle swarm optimization algorithms from Pareto-optimal solutions taking into account binary preference relations. …”
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Biodynamic Characteristics and Blood Pressure Effects of Stanford Type B Aortic Dissection Based on an Accurate Constitutive Model by Yiwen Wang, Libo Xin, Lijie Zhou, Xuefeng Wu, Jinong Zhang, Zhaoqi Wang

“…Using this validated model to define the hyperelastic properties of the aortic wall, a multiphysics coupling platform was constructed in COMSOL Multiphysics 6.2, integrating computational fluid dynamics (CFD) and fluid–structure interaction (FSI) algorithms. This framework systematically quantified the effects of blood pressure (bp) fluctuations on compressive stresses, von Mises stresses, and deformation of the intimal flap within the AD lesion region. …”
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DiffusionScore: A Framework for Assessing Institutional Research Impact Through Influence Diffusion by Gambhire Swati Sampatrao, Anisha Khetan, Nithin Nagaraj, Snehanshu Saha, Sudeepa Roy Dey, Archana Mathur

“…The recent ranking systems evaluate the reputation of academic institutions by employing network-based algorithms, like Page Rank which examine the citation network at the institution level. …”
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A Resting ECG Screening Protocol Improved with Artificial Intelligence for the Early Detection of Cardiovascular Risk in Athletes by Luiza Camelia Nechita, Dana Tutunaru, Aurel Nechita, Andreea Elena Voipan, Daniel Voipan, Anca Mirela Ionescu, Teodora Simina Drăgoiu, Carmina Liana Musat

“…<b>Methods:</b> For each of the six sports, resting 12-lead ECGs from healthy children and junior athletes were analyzed using AI algorithms trained on annotated datasets. Parameters included the QTc intervals, PR intervals, and QRS duration. …”
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